[Retracted] Detecting and Extracting Brain Hemorrhages from CT Images Using Generative Convolutional Imaging Scheme

Algorithm 1

IGACM on CT Image Analysis.

	Input: Brain CT Image Dataset,
	Output: Diagnosed CT slices
	Begin
	Step 1: Initiate and preprocess,
	Step 2: Call Haar Wavelet Transform for texture based Segmentation
	Step 3: Set CNN layer functions and filters
	Step 4: Train the dataset as sampled knowledge base
	Step 5: Compute the outcomes of CNN as given in equations (1)–(4)
	Step 6: Initiate GAN tuning functions for generating new CT Test samples as given in equation (5)
	Step 7: Redefine the CNN layers to improve classifier accuracy
	Step 8: Recall CNN pooling, max and ReLU functions to get
	Optimal symptoms from brain CT slices.
	Step 9: Store the computed results in neural memory cells
	Step 10: Recall the stored events for next computations
	Step 11: Do for all CT image segments
	End